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Psychosomatic Medicine 66:679-683 (2004)
© 2004 American Psychosomatic Society

ORIGINAL ARTICLES

Relationship Between Depression and C-Reactive Protein in a Screening Population

Kevin M. Douglas, MD, Allen J. Taylor, MD and Patrick G. O’Malley, MD MPH

From General Internal Medicine (K.M.D., P.G.O.) and Cardiology (A.J.T.), Department of Medicine, Walter Reed Army Medical Center, Washington, DC, and the Uniformed Services University of the Health Sciences, Bethesda, Maryland.

Address correspondence and reprint requests to Kevin M. Douglas, MD, Assistant Professor of Medicine, General Internal Medicine Service, Department of Medicine, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814-4799. E-mail: kevin.douglas{at}na.amedd.army.mil


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
BACKGROUND: Both depression and C-reactive protein (CRP) are markers of increased risk for cardiovascular events. This study examined the relationship between CRP and depression in a cohort of participants undergoing a periodic physical to assess potential for interaction as either mediation or confounding of effect on cardiovascular risk.

METHODS: We conducted a cross-sectional study of a cohort of 696 consenting, active duty US Army personnel undergoing a periodic physical. We measured depression using the Patient Health Questionnaire-9, the depression module of the self-administered version of the Primary Care Evaluation of Mental Disorders (PRIME-MD). We used a highly sensitive assay to measure CRP.

RESULTS: The mean age in the cohort was 44 years (SD ± 3; 82% male). The mean CRP level was 1.7 mg/l (range, 0.3–9.9; SD ± 1.6 mg/l). Depression scores ranged from 0 to 26 with a mean of 2 (SD ± 3). Depression scores correlated with prevalences of major depressive disorder and of any depressive disorder of 3.3% and 15%, respectively. Depression scores correlated positively with CRP levels (r = 0.085; p = .028), as did other variables known to be associated with CRP: body mass index (BMI; r = 0.36), insulin levels (r = 0.22), mean arterial pressure (r = 0.21), triglycerides (r = 0.18), exercise (r = –0.12), female sex (r = 0.097), current smoking status (r = 0.08), and high density lipoprotein (r = –0.09). After controlling only for BMI, the relationship between depression and CRP lost statistical significance among women (adjusted r = 0.08; p = .37), among men (adjusted r = –0.11; p = .8), and overall (adjusted r = 0.047; p = .219).

CONCLUSION: Depressive symptoms are only weakly correlated with CRP. However, after adjusting for BMI, we found no significant relationship between CRP and depression. The relationship between depression and clinical coronary disease is unlikely to be explained through direct effects on CRP levels, but may be mediated by BMI.

Key Words: C-reactive protein, • inflammation, • depression, • obesity, • body mass, • cardiovascular disease.

Abbreviations: CRP = C-reactive protein;; BMI = body mass index;; PHQ-9 = 9-question depression module of the Patient Health Questionnaire.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Depression has been demonstrated to have causal associations with incident coronary disease (1–12), and has been demonstrated to be associated with higher risk of adverse outcomes after acute coronary events (11,13,14). Several hypotheses grounded in previous laboratory and clinical research have been proposed to explain such associations: increased platelet reactivity, decreased heart rate variability, poor adherence to efficacious therapies, or atherogenesis itself (10). Because depression is also associated with immunological changes (15), it is also possible that depression may affect the development of coronary disease through systemic inflammation. For example, high sensitivity C-reactive protein (CRP), a serologic marker of systemic inflammation, has been recently discovered to be a strong independent risk marker for coronary artery disease (16).

Several previous studies have examined the relationship between depression and CRP (15,17–22). However, much of the literature to date has been limited by retrospective, case-control study design and potential uncontrolled confounding (15,18,19). In addition, very few studies have examined the relationship between depression and CRP in a healthy, nonelderly population (21,22).

The objective of this study was to explore the independent relationship between symptoms of depression and CRP in an asymptomatic middle-aged screening population. Such information could shed light on the question of whether depression is associated with adverse cardiovascular outcomes through inflammatory mediation. Our hypothesis was that depression scores would independently and positively correlate directly with levels of inflammation, as measured by CRP.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
This study was conducted as part of the Prospective Army Coronary Calcium project, the methods of which have been previously published (23). Briefly, all active duty US Army personnel age 39 to 45 years and stationed within the Washington, DC, area were recruited at the time of a periodic, Army-mandated physical examination. Patients who had a history of coronary heart disease or who indicated a history of angina pectoris by the Rose questionnaire (24) were ineligible. Participation in the protocol was entirely voluntary. Eligible patients who were approached for consent were explicitly informed that nonparticipation in the study protocol would in no way affect their future medical care of military career, and that information obtained as a participant would be strictly confidential. The Department of Clinical Investigation and Human Use Committee of Walter Reed Army Medical Center (Washington, DC) approved the protocol.

Each participant provided details of their medical history, including a history of hypertension, diabetes mellitus, hypercholesterolemia, and psychiatric disorders and a family history of premature cardiovascular disease. Smoking was self-reported.

Height and weight, body mass index (BMI), and blood pressure were measured in standard fashion. Fasting blood was collected for the measurement of serum glucose, glycosylated hemoglobin, insulin, and high-sensitivity CRP. Low-density lipoprotein cholesterol was measured using a direct assay.

Measurement of CRP
Measurement of CRP was performed on fasting serum with an ultrasensitive assay using particle-enhanced immunoturbidimetric latex agglutination methodology (25). A technician blinded to all clinical and serologic data performed the testing. Previous use of this assay within our laboratory demonstrated a high degree of measurement reproducibility (intraclass correlation coefficient of 0.998; 26).

Assessment of Depression
Depression was measured using the 9-question depression module of the Patient Health Questionnaire (PHQ-9), which is the self-administered version of the Primary Care Evaluation of Mental Disorders (PRIME-MD). Both the PRIME-MD and the PHQ-9 have been validated using cohorts that included the same military medical center from which our current cohort was derived (27,28). Depressive symptoms endorsed on the PHQ-9 must have been present over the period of the past 2 weeks. The survey was completed on the same day subjects underwent serologic studies (including CRP). Continuous scores for depression were created based on the cumulative number and severity of symptoms endorsed in each domain. This scoring method has been validated as both a diagnostic tool and a marker of change in depressive status (28). These scores correlate strongly with mental health functional status in the cohort from which the present study was derived, as previously reported (29).

Statistical Analysis
C-reactive protein levels greater than 10 mg/l were assumed to represent acute or chronic infection or inflammation and were excluded from the analysis. The remaining CRP values were then pseudonormalized using the natural log function. Continuous variables were compared using a t test for independent groups. Correlations were performed using Pearson {rho} coefficient. Stepwise multiple regression was used to assess the relative influence of multiple positively and negatively associated variables with respect to the dependent variable, CRP. A two-tailed p value ≤ .05 was considered significant.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 NOTES
 REFERENCES
 
The demographics, cardiovascular risk factors, and depressive symptomatology for the 696 participants are shown in Table 1. The group was predominantly well educated. White men composed the majority of the cohort, although 18% of participants were women and 31% were nonwhite. Based on the Framingham Risk Index, the 5-year predicted coronary heart disease risk of the study group was relatively low (2 ± 1.6%).


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  		TABLE 1. Demographics, Coronary Artery Disease Risk Profile, and Depression Prevalence (N = 696)
 
High sensitivity CRP levels were skewed toward lower levels, with 13% of measurements greater than 3 mg/dl and an overall mean of 1.7 ± 1.6 mg/dl. Depression scores on the PHQ-9 demonstrated a low level of depressive symptoms overall, with a mean score of 2 ± 3. Three percent of participants had scores correlating with a diagnosis of major depression, and 15% had scores correlating with depression not otherwise specified (NOS).

Table 2 lists variables measured in these studies that have already been documented to correlate with CRP in other studies. Depression scores correlated positively with CRP levels (r = 0.085; p = .028).


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  		TABLE 2. Variables With Documented Associations With hs-CRP, and Their Correlation With hs-CRP in This Study Sample
 
Stepwise multiple regression of the variables in Table 2 yielded a model in which only four variables remained with significant influence on hs-CRP variation (Table 3). This analysis demonstrated that the strongest predictor of CRP was BMI followed by sex, mean arterial pressure, and fasting insulin level. Depression was not independently associated with CRP in this model.


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  		TABLE 3. Linear Regression Models Explaining the Variance of hs-CRP Among 696 Participants in a Cardiovascular Screening Program
 
Controlling only for BMI, the relationship between depression and CRP lost statistical significance among women (adjusted r = 0.08; p = .37), and men (adjusted r = –0.11; p = .8) and overall (adjusted r = 0.047; p = .219).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
NOTES
 REFERENCES
 
Studies have demonstrated an increased risk for cardiovascular morbidity and mortality associated with depression (1–14), yet little is known of the mechanism explaining such an association. Our study indicates that total depression score does not independently correlate with CRP, and that any correlation between depression score and CRP may be explained by a relationship with BMI.

Several studies have previously examined the association between CRP and depression, and the preponderance of evidence supports the conclusion that depression is associated with CRP but is confounded or mediated by other variables, particularly those that reflect fat mass (17–20,22).

In a small (N = 64) case-control study in 1996, Sluzewska et al. (15) showed that CRP levels were significantly higher in patients with major depression compared with normal controls. No adjustment for possible confounders was performed, however.

In 2002, Kop et al. (17) screened 4268 elderly subjects (age 72 ± 5 years; 61% female) for depression while simultaneously measuring CRP levels and found a significantly positive difference between depressed and nondepressed subjects (3.51 ± 0.21 vs. 3.31 ± 0.10 mg/l; p = .0008). This relationship disappeared after adjusting for other variables, including weight.

Timeier et al. (19) conducted a case-control study in Rotterdam involving 263 elderly subjects with depressive symptoms, once again finding a positive correlation between depression and CRP levels. This relationship disappeared after adjustment for potential confounders (smoking, stroke, functional disability, and cognitive score).

Whereas these studies reported a positive correlation between CRP and depression (15,17,19) that lost statistical significance after adjustment for potential confounders, one small (N = 100) case-control study (18; 68% female; mean age, 30 years) found a persistently significant correlation between CRP and depression peculiar to the obese subgroup of patients (BMI >30). However, they also reported that when adjusting for BMI as a continuous variable, depression was no longer significantly correlated with CRP. It is very likely that using only a dichotomous measure of BMI was insufficient to control for the effect of BMI on CRP.

In 2003, Penninx et al. (20) performed a large (N = 3024) cross-sectional analysis of a nonclinical elderly population (70–79 years old) examining the relationship between depression and inflammation. After dichotomizing the scores of their depression scale and stratifying the CRP levels into quartiles, they demonstrated a correlation between the depressed group and the CRP measurements. After controlling for potential confounders, including body fat mass, this relationship persisted, but only for the highest quartile of CRP levels, not for the first 3. Excessive categorical stratification of what were initially continuous variables may have increased the likelihood of a Type I error in this study. In addition, failure to set exclusion criteria for the highest CRP levels may have permitted CRP levels representing acute or chronic inflammatory disease states to bias the results and may explain why only the highest quartile of CRP levels demonstrated a persistently significant association.

Steptoe et al. (21) conducted a similarly designed cross-sectional analysis examining the relationship between depression scale scores and CRP in a nonclinical middle-aged population in Great Britain. Even without controlling for confounders, the researchers found no relationship between depressive symptoms and CRP levels. However, the power of this negative study may have been limited by its smaller sample size (N = 226) and by dichotomization of the depression scores.

Based on data obtained from a small (N = 100) case-control study, Miller et al. (22) recently performed structural equation modeling suggesting that body mass may mediate rather than confound the relationship between depression and CRP. Although not yet confirmed through other studies, this hypothesis is nevertheless an intriguing way to make sense of multiple interrelated collinear variables. Strengths of our study include a prospective method of data collection, which is less vulnerable to bias than retrospective cohort data collection; systematic and precise measurement of variables while blinded to the status of other key variables; use of a validated depressive measurement tool with demonstrated internal validity within the population in which it was used; and the large size of the study which permitted the power to rigorously control for potential confounding. Using a two-tailed {alpha} of 0.05 and a a of 0.20, our sample size was sufficient to detect a correlation with a coefficient stronger than ±0.11 should one have existed. Because our hypothesis concerned a positive correlation, our data had a power of 0.82 to detect any correlation stronger than >0.09. It is possible that there is a correlation our data were not powered to detect, but we think that a correlation <0.15 would not be clinically significant. External validity is supported by the consistency with other studies in corroborating associations between CRP and variables such as body mass (30–38), female sex (41), blood pressure (33,34,39), and insulin levels (30,32,33,37,38).

There are several limitations of this study. First, there were low levels of depressive scores among participants that could have led to an underestimation of the size of the relation between depression and inflammation. It is also possible that although the PHQ-9 depressive score has been demonstrated to change with clinical change in depressive status (17), this was demonstrated in a clinically depressed population, and it may not be sensitive to dynamic depressive states in nondepressed populations. This may lead to an underestimation of any association. However, to our knowledge, there is no other tool available that has been validated as a marker of dynamic depressive states in a nonclinical population. Second, this study was performed in a population with a narrow age range (39–50 years old) and may not be generalizable to other age groups. On the other hand, this may also control for the effect of age on CRP. Third, we specifically focus on CRP because of its special relevance to cardiovascular risk as demonstrated in the recent literature. However, CRP is a crude marker for systemic inflammation and clearly not as direct a measure of the inflammatory process as certain cytokines. It is possible, therefore, that other more direct serologic measures of inflammation might have stronger and more persistent associations with depression (46). Fourth, although we find the stepwise regression model interesting, we regard it primarily as an exploratory strategy in investigating the possible relationships between CRP and other variables. We recognize the possibility that our model may overestimate certain relationships by chance. Nevertheless, we are confident in the ability of regression modeling to identify accurately which variables are not significant, such as the depression score in this case. Last, although these data were collected prospectively, it is still a cross-sectional analysis. An ideal analysis would be the assessment of change in depressive scores and CRP over time, and their correlation and interaction as they relate to cardiovascular events.

In this consecutive sample of asymptomatic, healthy, middle-aged men and women, depressive scores weakly correlated with CRP. However, after adjusting for BMI, we found no significant relationship between CRP and depression. The relationship between depression and clinical coronary disease is unlikely to be explained through direct effects on CRP. It is possible that associations between depression and CRP (and therefore cardiovascular outcomes) might be confounded or mediated by BMI.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
REFERENCES
 
The views expressed here are those of the authors only and are not to be construed as those of the Department of the Army or the Department of Defense.

Received for publication December 12, 2003.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 

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